Automated Image System for Scoring Changes in Quantitative Interstitial Lung Disease

1. A method for scoring changes in Quantitative Interstitial Lung Disease (QILD), comprising: uploading a plurality of CT images of a patient's lung; filtering the uploaded images to minimize cross-site variability within images; generating a QILD score for each image based on selected features within the image; and calculating a transition between QILD scores within the plurality of CT images.

2. A method as recited in claim 1 , further comprising: sampling from a grid of pixels or voxels within the CT images.

3. A method as recited in claim 2 , further comprising: classifying individual pixels or voxels within said downloaded images based on one or more selected texture features; and wherein the QILD score is calculated as the quotient of a total number of pixels or voxels within a CT image that are classified as a disease type by a total number (counts) of grid samples within the CT image.

4. A method as recited in claim 1 , wherein calculating a transition between QILD scores comprises calculating transitional changes of hierarchical severity within the image.

5. A method as recited in claim 4 , wherein the transitional changes of hierarchical severity are calculated using a Markov Chain.

6. A method as recited in claim 2 , wherein classifying individual pixels or voxels is a function of a classifier model built using Support Vector Machine (SVM). programming.

7. A method as recited in claim 1 , wherein the transition between QILD scores is used for estimating a transitional change in one or more of: fibrotic reticulation, ground glass and normal patterns associated with the patient's lung.

8. A method as recited in claim 1 , wherein calculating a transition between QILD scores comprises generating a Markov Chain Transition Matrix (MCTM) of the QILD scores.

9. A method as recited in claim 8 , wherein the MCTM is a function of the fibrotic reticulation, ground glass and normal patterns associated with the patient's lung.

10. A system for scoring changes in Quantitative Interstitial Lung Disease (QILD), comprising: a processor; and programming executable on said processor for: uploading a plurality of CT images of a patient's lung; filtering the uploaded images to minimize cross-site variability within images; generating a QILD score for each image based on selected features within the image; and calculating a transition between QILD scores within the plurality of CT images.

11. A system as recited in claim 10 , further comprising: sampling from a grid of pixels or voxels within the CT images.

12. A system as recited in claim 11 , said programming further configured for: classifying individual pixels or voxels within said downloaded images based on one or more selected texture features; and wherein the QILD score is calculated as the quotient of a total number of pixels or voxels within a CT image that are classified as a disease type by a total number (counts) of grid samples within the CT image.

13. A system as recited in claim 10 , wherein calculating a transition between QILD scores comprises calculating transitional changes of hierarchical severity within the image.

14. A system as recited in claim 13 , wherein the transitional changes of hierarchical severity are calculated using a Markov Chain.

15. A system as recited in claim 11 , wherein classifying individual pixels or voxels is a function of a classifier model built using Support Vector Machine (SVM) programming.

16. A system as recited in claim 10 , wherein the transition between QILD scores is used for estimating a transitional change in one or more of: fibrotic reticulation, ground glass and normal patterns associated with the patient's lung.

17. A system as recited in claim 10 , wherein calculating a transition between QILD scores comprises generating a Markov Chain Transition Matrix (MCTM) of the QILD scores.

18. A system as recited in claim 17 , wherein the MCTM is a function of the fibrotic reticulation, ground glass and normal patterns associated with the patient's lung.

19. A system for scoring changes in Quantitative Interstitial Lung Disease (QILD), comprising: a processor; and programming executable on said processor for: uploading a plurality of CT images of a patient's lung; filtering the uploaded images to minimize cross-site variability within images; sampling from a grid of pixels or voxels within the CT images; classifying individual pixels or voxels within said downloaded images based on one or more selected texture features; generating a QILD score for each image based on selected features within the image; wherein the QILD score is calculated as the quotient of a total number of pixels or voxels within a CT image that are classified as a disease type by a total number (counts) of grid samples within the CT image; and calculating a transition between QILD scores within the plurality of CT images.

20. A system as recited in claim 19 : wherein calculating a transition between QILD scores comprises calculating transitional changes of hierarchical severity within the image; and wherein the transitional changes of hierarchical severity are calculated by generating a Markov Chain Transition Matrix (MCTM) of the QILD scores.

21. A system as recited in claim 20 , wherein the MCTM is a function of the fibrotic reticulation, ground glass and normal patterns associated with the patient's lung.

22. A system as recited in claim 19 , wherein filtering comprises filtering noise as a function of geometric, texture, and noised images associated with the CT images.

23. A system as recited in claim 19 , wherein the classified disease types comprise one or more of: fibrotic reticulation, ground glass and normal patterns.

24. A system as recited in claim 23 , wherein the fibrotic reticulation disease type comprises is combined patterns of lung fibrosis and honeycomb.

25. A system as recited in claim 19 , wherein the QILD score is the sum of Quantitative Fibrotic Reticulation (QFR), Quantitative Ground Glass (QGG), and Quantitative Normal Lung (QNL) scores.

26. A system as recited in claim 25 , where the QFR score is the sum of quantitative lung fibrosis and honeycomb.